作者：
Oh, Jae C.EECS
Syracuse University Syracuse NY 13244 United States
This paper discusses how evolutionary algorithms are related to multi-agent systems and the possibility of military applications using the two disciplines. In particular, we present a game theoretic model for multi-ag...
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ISBN:
(纸本)0819462845
This paper discusses how evolutionary algorithms are related to multi-agent systems and the possibility of military applications using the two disciplines. In particular, we present a game theoretic model for multi-agent resource distribution and allocation where agents in the environment must help each other to survive. Each agent maintains a set of variables representing representing actual friendship and perceived friendship. The model directly addresses problems in reputation management schemes in multi-agent systems and Peer-to-Peer distributed systems. We present algorithms based on evolutionary game process for maintaining the friendship values as well as a utility equation used in each agent's decision making. For an application problem, we adapted our formal model to the military coalition support problem in peace-keeping missions. Simulation results show that efficient resource allocation and sharing with minimum communication cost is achieved without centralized control.
In this work we present a comparison of several Artificial Neural Networks weights initialization methods based on evolutionary algorithms. We have tested these methods on three datasets: KEEL regression problems, ran...
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ISBN:
(纸本)9788897999324
In this work we present a comparison of several Artificial Neural Networks weights initialization methods based on evolutionary algorithms. We have tested these methods on three datasets: KEEL regression problems, random synthetic dataset and a dataset of concentration of different chemical species from the Bioethanol To Olefins process. Results demonstrated that the tuning of neural networks initial weights improves significantly their performance compared to a random initialization. In addition, several crossover algorithms were tested to identify the best one for the present objective. In the post-hoc analysis there were found significant differences between the implemented crossover algorithms when the network has four or more inputs.
Hydrodynamic optimization design of the bend pipe from pump using theNavier-Stokes solver and evolutionary algorithms was conducted. The minimization of the totalpressure loss of the bend pipe was chosen as the design...
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Hydrodynamic optimization design of the bend pipe from pump using theNavier-Stokes solver and evolutionary algorithms was conducted. The minimization of the totalpressure loss of the bend pipe was chosen as the design object in order to obtain the uniform exitflows through suppressing the secondary flows. The 3-D Navier-Stokes solver was applied to evaluatethe hydrodynamic performance of the bend-pipe flows. A 7th-order Bezier curve was used toparameterize the meridional section and elliptic representation was adopted to represent thecross-section profiles of the bend pipe. evolutionary algorithms were applied in optimization. Theobtained results show that the designed bend pipe shape has much more uniform exit flows comparedwith the initial one and much weaker secondary flows, and that the evolutionary algorithms and CFDtechnique are the powerful optimization tools for the fluid machinery desiga
The task planning of satellite-ground time synchronization (SGTSTP) is a complex many-objective ground station scheduling problem. In this paper, we first provide a mathematical formulation of SGTSTP. To solve this pr...
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Smart technology have end up an increasing number of vital in today's rapidly evolving generation panorama. Automation, records-pushed decision-making, and streamlined operations are all being revolutionized by me...
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The design of RF cavities is a multivariate multi-objective problem. Manual optimisation is poorly suited to this class of investigation, and the use of numerical methods results in a non-differentiable problem. Thus ...
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ISBN:
(纸本)9789290833529
The design of RF cavities is a multivariate multi-objective problem. Manual optimisation is poorly suited to this class of investigation, and the use of numerical methods results in a non-differentiable problem. Thus the only reliable optimisation algorithms employ heuristic methods. Using an evolutionary algorithm guided by Pareto ranking methods, a crab cavity design can be optimised for transverse voltage (VT) while maintaining acceptable surface fields and the correct operating frequency. evolutionary algorithms are an example of a parallel meta-heuristic search technique inspired by natural evolution. They allow complex, epistatic (non-linear) and multimodal (multiple optima and/or sub-optima) optimization problems to be efficiently explored. Using the concept of domination the solutions can be ordered into Pareto fronts. The first of which contains a set of cavity designs for which no one objective (e.g. the transverse voltage) can be improved without decrementing other objectives.
This paper studies the use of machine learning models for multiobjective optimization of vaccinations used to control an epidemic spreading in a graph representing contacts between individuals. Graph nodes are pa...
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To obtain the expertise to correctly perform minimally-invasive vascular interventions thorough training is required. Training using simulation systems are increasingly becoming an accepted methodology. Recently, a mi...
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Randomized search heuristics like evolutionary algorithms are mostly applied to problems whose structure is not completely known but also to combinatorial optimization problems. Practitioners report surprising success...
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ISBN:
(纸本)3540006230
Randomized search heuristics like evolutionary algorithms are mostly applied to problems whose structure is not completely known but also to combinatorial optimization problems. Practitioners report surprising successes but almost no results with theoretically well-founded analyses exist. Such an analysis is started in this paper for a fundamental evolutionary algorithm and the well-known maximum matching problem. It is proven that the evolutionary algorithm is a polynomial-time randomized approximation scheme (PRAS) for this optimization problem, although the algorithm does not employ the idea of augmenting paths. Moreover, for very simple graphs it is proved that the expected optimization time of the algorithm is polynomially bounded and bipartite graphs are constructed where this time grows exponentially.
Lens system design makes extensive use of optimization techniques to improve the performance of an optical system. We know that designing a lens system is a complex task currently done by experienced optical designers...
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Lens system design makes extensive use of optimization techniques to improve the performance of an optical system. We know that designing a lens system is a complex task currently done by experienced optical designers, using specialized optical design software tools. In order to contribute to this particular field, this paper presents a comparison between lens design done by optical designers and evolutionary algorithms lens based design. evolutionary algorithms consist in population-based global search methods inspired by natural evolution. They are recognized to be particularly efficient for complex non-linear optimization problems. Given the non-linear nature of lens design as an optimization process, evolutionary algorithms are good candidates for automating this task. The evolutionary algorithms were applied to the monochromatic quartet that was presented to expert participants at the International Lens Design Conference in 1990 (a friendly competition). Comparative results demonstrate that the evolutionary approach is able to find solutions slightly better than those presented at the competition. Then a real-life imaging problem is tackled. Results show that an evolutionary algorithm is again able to discover lens systems comparable to design done after a reasonable effort by experts. This paper presents an analysis of this approach for automatic lens design from a real-life optical design point of view.
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